AI/ML Engineer Skill Level 2 - FFPP-8953

Nyla Technology Solutions

• $216K — $255K *
Aerospace & Defense
15+ years of experience
Job Overview by Ladders

Qualifications

  • Active TS/SCI polygraph security clearance required
  • Bachelor's degree in a technical field, with required years of experience, or equivalent experience without degree
  • 17+ years of professional software engineering experience or Master's with 10+ years
  • Strong experience with applied machine learning frameworks like PyTorch or TensorFlow
  • Skills in data engineering, statistical analysis, and prototype-to-production engineering

Responsibilities

  • Design and build scalable AI/ML models for critical applications
  • Oversee entire model lifecycle from data pipelines to production deployment
  • Evaluate and refine models through iterative feedback and retraining
  • Lead test and evaluation protocols for AI systems
  • Communicate complex AI concepts to cross-functional teams

Benefits

  • Comprehensive benefits package
  • Discretionary bonus compensation potentially available
  • Collaborative work environment with cross-functional teams
  • Opportunities for continued learning and professional development
  • Participation in high-stakes AI initiatives
Full Job Description
Job Description

ACTIVE SECURITY CLEARANCE AT THE TS/SCI POLYGRAPH LEVEL IS REQUIRED

We are seeking a visionary, inventive Artificial Intelligence / Machine Learning (AI/ML) Engineer to design, build, test, and productize advanced models that solve high-stakes challenges. In this role, you won't just train models in isolation-you will transform data science prototypes into production-ready, scalable AI solutions. You will oversee the complete lifecycle: architecting data pipelines, selecting optimal representations, running statistical analyses, and continuously refining models through iterative feedback and retraining loops. As a technical leader and primary subject matter expert, you will guide test and evaluation protocols, evaluate data distribution shifts, and ensure our AI systems deliver accurate, mission-critical predictions at scale.

The annual base salary range for this role is $216,000-$255,000 (USD) , which does not include discretionary bonus compensation or our comprehensive benefits package. Actual compensation offered to the successful candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level, among other things.

Required Skills

Applied Machine Learning: Demonstrated experience selecting, training, evaluating, and productizing AI/ML models using standard frameworks (e.g., PyTorch, TensorFlow) and ML libraries.

Model Lifecycle & MLOps: Hands-on experience in pipeline interaction, data modeling, feature selection, model verification/validation, monitoring, and iterative retraining based on feedback loops.

Data Engineering & Statistical Analysis: Strong capabilities in statistical analysis, detecting data distribution shifts, and converting raw datasets into effective data representations for ML algorithms.

Prototype-to-Production Engineering: Proven ability to transform experimental data science prototypes into scalable, performant production systems with proper system integration oversight.

Software Foundations & Test Protocols: Sound understanding of application development concepts, data structures, software architecture, and running standard test/evaluation protocols.

Communication & Technical Leadership: Excellent analytical, problem-solving, and presentation skills to serve as a primary POC for AI initiatives and guide cross-functional teams.

Education: Bachelor's Degree in Computer Science, Computer Engineering, Software Engineering, or a related technical discipline, PLUS 17+ years of professional software engineering experience OR Master's Degree PLUS 10+ years of professional software engineering experience OR High School Diploma / GED, PLUS 22+ years of hands-on technical software development experience in lieu of a degree.

Desired Skills

Multi-Language Mastery: Advanced proficiency in multiple programming languages, such as Python, Java, C, C++, or R.

Advanced MLOps & Infrastructure: Deep familiarity with cloud-based AI deployments, automated model scheduling, data governance, and automated CI/CD pipelines for ML models.

Distributed Team Leadership: Direct experience leading geographically dispersed engineering teams and driving collaborative AI research initiatives.

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